# US 9,519,872 B2 · Systematic discovery of business ontology > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 9,519,872 B2 - Document ID: US9519872B2 - Status: Granted - Kind: B2 - Application number: 13/974,318 - Filed: 2013-08-23 - Published: 2015-02-26 - Granted: 2016-12-13 - Earliest claimed: 2013-08-23 - Assignees: Wal-Mart Stores, Inc. - Applicants: Wal-Mart Stores, Inc. - Inventors: Gary Dewayne Griggs - Web page: https://patentgrep.com/patent/US9519872B2 ## CPC - G06Q 10/00: Administration; Management - G06F 16/244: {Grouping and aggregation} - G06F 16/285: {Clustering or classification} - G06F 16/35: Clustering; Classification - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A system is provided that implements a more systematic process for obtaining business knowledge that is more efficient and timely. The process automatically reads business documents and produces a business ontology. In one implementation, the process dissects documents into sentences or collection of words that most resembles a sentence. Natural language processing algorithms may be used to identify the role of term within a sentence. Terms and associations resulting from the document analysis are used to specify a business ontology which can be then used to provide input to a software design process, among other business uses. ## Claims ### Claim 1 A system for determining a business ontology, the system comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to: perform an analysis of a plurality of business documents, wherein the analysis comprises: establishing an analysis scope that includes the plurality of business documents; determining a plurality of sentences within the plurality of business documents within the analysis scope, including separating the sentences for analysis; identifying terms and associations between terms within each separated sentence of the plurality of sentences, including determining a proximity between at least two of the terms within at least one sentence of the separated sentences, the proximity including a sentence proximity association for terms of the identified terms occurring in the same sentence but not in a same term group, a term proximity association for identifying actions acted upon terms of the identified terms by other terms, and a document proximity association for all verbs in the same business document of the plurality of business documents; analyzing the associations including the sentence proximity association, the term proximity association, and the document proximity association; after analyzing the terms and associations, identifying frequently-used terms and associations within the plurality of sentences used most within the scope; and determining a business ontology based on the identified frequently-used terms and associations within the plurality of sentences among the plurality of business documents. ### Claim 2 (depends on 1) The system according to claim 1, wherein the processor groups terms into term groups. ### Claim 3 (depends on 1) The system according to claim 1, wherein the proximity is at least one of a group comprising a former proximity and a latter proximity. ### Claim 4 (depends on 1) The system according to claim 1, wherein the processor determines an association by a proximity between at least two of the terms within at least one document. ### Claim 5 (depends on 1) The system according to claim 1, wherein the processor determines an association by a verb between at least two of the terms. ### Claim 6 (depends on 1) The system according to claim 1, wherein the processor determines an aspect of software using the determined business ontology. ### Claim 7 (depends on 6) The system according to claim 6, wherein the processor determines an information model using the determined business ontology. ### Claim 8 (depends on 1) The system according to claim 1, wherein the processor groups terms and associations together based on their meaning. ### Claim 9 (depends on 1) The system according to claim 1, wherein the processor stores, in the memory, a database including the identified terms and associations. ### Claim 10 A method for determining a business ontology, the method comprising acts of: performing an analysis by a computer system of a plurality of business documents, wherein the analysis comprises acts of: establishing an analysis scope that includes the plurality of business documents; determining a plurality of sentences within the plurality of business documents within the analysis scope, including separating the sentences for analysis; identifying terms and associations between terms within each separated sentence of the plurality of sentences, including determining a proximity between at least two of the terms within at least one sentence of the separated sentences, the proximity including a sentence proximity association for terms of the identified terms occurring in the same sentence but not in a same term group, a term proximity association for identifying actions acted upon terms of the identified terms by other terms, and a document proximity association for all verbs in the same business document of the plurality of business documents; analyzing the terms and associations including the sentence proximity association, the term proximity association, and the document proximity association; after analyzing the terms and associations, identifying frequently-used terms and associations within the plurality of sentences used most within the scope; and determining a business ontology based on the identified frequently-used terms and associations within the plurality of sentences among the plurality of business documents. ### Claim 11 (depends on 10) The method according to claim 10, further comprising an act of grouping terms into term groups. ### Claim 12 (depends on 10) The method according to claim 10, wherein the proximity is at least one of a group comprising a former proximity and a latter proximity. ### Claim 13 (depends on 10) The method according to claim 10, further comprising an act of determining an association by a proximity between at least two of the terms within at least one document. ### Claim 14 (depends on 10) The method according to claim 10, further comprising an act of determining an association by a verb between at least two of the terms. ### Claim 15 (depends on 10) The method according to claim 10, further comprising an act of determining an aspect of software using the determined business ontology. ### Claim 16 (depends on 15) The method according to claim 15, further comprising an act of determining an information model using the determined business ontology. ### Claim 17 (depends on 10) The method according to claim 10, further comprising an act of grouping terms and associations together based on their meaning. ### Claim 18 (depends on 10) The method according to claim 10, further comprising an act of storing, in a memory of the computer system, a database including the identified terms and associations.